Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A system comprising: a hardware processor; and a non-transitory computer-readable storage medium having stored thereon program instructions, the program instructions executable by the at least one hardware processor to: receive, using a first transceiver, a radio-frequency (RF) transmission from an RF device; and detect a second transceiver performing a relay or man-in-the-middle (MITM) attack by: detecting double-Automatic Gain Control (AGC) distortion effect in the received RF transmission by: finding and extracting a rise transient from a beginning to a start of a data region of the received RF transmission; estimating a differential AGC distortion caused by the receiver, based on the known output of an AGC circuit if the system; and determining whether the received RF transmission exhibits greater AGC distortion than the differential AGC distortion such as to indicate distortion from a relay or replay AGC stage of the second transceiver.
Wireless communication security. This invention addresses the problem of detecting relay or man-in-the-middle (MITM) attacks in radio-frequency (RF) transmissions. The system includes a hardware processor and a non-transitory computer-readable storage medium containing program instructions. When executed, these instructions enable the system to receive an RF transmission from an RF device using a first transceiver. The core of the invention lies in detecting a second transceiver performing a relay or MITM attack by identifying a specific distortion effect. This is achieved by detecting double-Automatic Gain Control (AGC) distortion. The system accomplishes this by finding and extracting a rise transient from the beginning to the start of the data region within the received RF transmission. It then estimates a differential AGC distortion that would be caused by the system's own AGC circuit. Finally, the system determines if the received RF transmission exhibits AGC distortion exceeding this estimated differential AGC distortion. Such an excess indicates distortion originating from a relay or replay AGC stage of the attacking second transceiver.
2. The system of claim 1 , wherein estimating the differential AGC distortion caused by the receiver and determining whether the received RF transmission exhibits greater AGC distortion than the differential AGC distortion includes measuring mean power of complex column sample vector.
This invention relates to wireless communication systems, specifically addressing the problem of automatic gain control (AGC) distortion in received radio frequency (RF) transmissions. AGC distortion occurs when the receiver's gain adjustment introduces nonlinearities, degrading signal quality. The system estimates the differential AGC distortion caused by the receiver and compares it to the distortion observed in the received RF transmission to assess signal integrity. The system measures the mean power of a complex column sample vector derived from the received signal. This measurement helps quantify the distortion introduced by the receiver's AGC mechanism. By comparing the observed distortion in the RF transmission to the estimated differential AGC distortion, the system determines whether the received signal exhibits excessive distortion that could impair communication performance. This comparison allows for real-time assessment of signal quality and potential adjustments to mitigate distortion effects. The invention improves signal processing in wireless receivers by providing a method to isolate and evaluate AGC-induced distortion, ensuring more accurate and reliable signal reception. This is particularly useful in environments where signal integrity is critical, such as in high-speed data transmission or low-power communication systems. The system's ability to measure and compare distortion levels enables adaptive adjustments to enhance overall communication reliability.
3. The system of claim 1 , wherein detecting double-AGC distortion further comprises: finding and extracting samples of the received RF transmission including: before the beginning of the rise transient; after a fall transient; and from frequencies out of a bandwidth of the received RF transmission during a data transmission section of the received RF transmission.
The system detects and mitigates double-AGC (Automatic Gain Control) distortion in radio frequency (RF) transmissions. Double-AGC distortion occurs when the gain control mechanism fails to adjust properly, causing signal amplitude fluctuations that degrade communication quality. The system analyzes the received RF transmission to identify and extract specific signal samples that indicate distortion. These samples are taken from three key regions: before the rise transient, after the fall transient, and from frequencies outside the transmission bandwidth during the data section. By examining these regions, the system can detect anomalies caused by improper gain adjustments. The extracted samples are then used to correct the distortion, ensuring stable signal reception. This approach improves signal integrity and reliability in RF communication systems, particularly in environments where gain control errors are prevalent. The system operates in real-time, dynamically adjusting to maintain optimal signal quality.
4. The system of claim 3 , wherein the samples are extracted by using a high pass filter with a cutoff frequency that is higher than the bandwidth of the received RF transmission.
A system for processing radio frequency (RF) transmissions addresses the challenge of extracting relevant signal components while mitigating interference and noise. The system includes a receiver configured to capture an RF transmission, which may contain both desired signal components and unwanted noise or interference. To isolate the desired components, the system employs a high-pass filter with a cutoff frequency set higher than the bandwidth of the received RF transmission. This filtering approach ensures that low-frequency noise and interference, which typically fall outside the signal bandwidth, are effectively removed. The filtered samples are then processed to extract the relevant signal information, improving signal quality and reliability. The system may also include additional components, such as an analog-to-digital converter (ADC) for digitizing the filtered signal and a processor for further analysis or decoding. By dynamically adjusting the cutoff frequency based on the transmission's bandwidth, the system optimizes performance across varying RF environments, ensuring robust signal extraction and minimizing distortion. This approach is particularly useful in applications where signal integrity is critical, such as wireless communications, radar systems, or signal intelligence.
5. The system of claim 1 , wherein detecting double-AGC distortion further comprises: determining that the received RF transmission was not relayed or replayed by determining that the received RF transmission was not previously distorted by a AGC stage of another RF device prior to the first RF receiver receiving the RF transmission.
This invention relates to radio frequency (RF) communication systems and addresses the problem of detecting distortion caused by automatic gain control (AGC) stages in RF transmissions. AGC stages in RF devices adjust signal strength to maintain optimal reception, but when a transmission is relayed or replayed through multiple devices, successive AGC stages can introduce cumulative distortion, degrading signal quality. The system detects such distortion by analyzing the received RF transmission to determine whether it has been previously processed by an AGC stage of another RF device before reaching the first RF receiver. If the transmission shows no signs of prior AGC distortion, it is concluded that the signal was not relayed or replayed, ensuring its integrity. The system may use signal analysis techniques, such as examining amplitude variations or comparing the signal against known distortion patterns, to identify the absence of prior AGC processing. This approach helps maintain signal fidelity in multi-hop or replayed transmission scenarios, improving communication reliability in RF networks.
6. The system of claim 1 , wherein detecting double-AGC distortion further comprises: training one or more machine learning classifiers for detecting double-AGC distortion with a set of clean signals, which are signals that not distorted by an AGC circuit.
This invention relates to signal processing systems designed to detect and mitigate double-AGC (Automatic Gain Control) distortion in communication signals. Double-AGC distortion occurs when multiple AGC circuits sequentially process a signal, causing unintended amplitude variations and degrading signal quality. The system addresses this problem by using machine learning to identify and correct such distortions. The system includes a training phase where one or more machine learning classifiers are trained using a set of clean signals—signals that have not been distorted by an AGC circuit. These classifiers are then deployed to analyze incoming signals and detect instances of double-AGC distortion. The training process involves feeding the classifiers with labeled data, where clean signals are used to establish a baseline for normal signal behavior. The classifiers learn to distinguish between clean signals and those affected by double-AGC distortion, enabling accurate detection in real-world applications. By leveraging machine learning, the system improves upon traditional detection methods, which often rely on fixed thresholds or heuristic rules. The trained classifiers can adapt to varying signal conditions and provide more reliable distortion detection. This approach enhances signal integrity in communication systems where multiple AGC stages are present, such as in wireless networks, audio processing, or digital broadcasting. The overall goal is to maintain signal quality and ensure accurate data transmission.
7. The system of claim 1 , wherein detecting double-AGC distortion further comprises at least one of: determining a noise mean power; assuming an underlying Rayleigh model and performing a parameter estimation by a Maximum Likelihood or a Method of Moments approach; or assuming a real normal model and calculating variances, an average and squared root.
The invention relates to a system for detecting and mitigating double-AGC (Automatic Gain Control) distortion in communication signals. Double-AGC distortion occurs when multiple AGC stages in a receiver chain introduce nonlinearities, degrading signal quality. The system addresses this by analyzing signal characteristics to identify and correct such distortions. The system includes a receiver with multiple AGC stages and a processing module that detects distortion by evaluating signal power and statistical properties. Specifically, it determines the noise mean power to assess baseline signal conditions. Alternatively, it assumes an underlying Rayleigh distribution for the signal and performs parameter estimation using Maximum Likelihood or Method of Moments techniques to identify distortion patterns. Another approach involves assuming a real normal model for the signal, where variances, averages, and squared root calculations are used to detect deviations indicative of double-AGC effects. Once distortion is detected, the system applies corrective measures, such as adjusting gain settings or applying signal processing algorithms, to restore signal integrity. The system is particularly useful in wireless communication systems where multiple AGC stages are common, ensuring reliable signal reception and reducing errors caused by distortion.
8. A method comprising operating at least one hardware processor for: receiving, using a first transceiver, a radio-frequency (RF) transmission from an RF device; and detecting a second transceiver performing a relay or man-in-the-middle (MITM) attack by: detecting double-Automatic Gain Control (AGC) distortion effect in the received RF transmission by: finding and extracting a rise transient from a beginning to a start of a data region of the received RF transmission; estimating a differential AGC distortion caused by the receiver, based on the known output of an AGC circuit if the system; and determining whether the received RF transmission exhibits greater AGC distortion than the differential AGC distortion such as to indicate distortion from a relay or replay AGC stage of the second transceiver.
This invention relates to detecting relay or man-in-the-middle (MITM) attacks in radio-frequency (RF) communications by analyzing Automatic Gain Control (AGC) distortion effects. The problem addressed is the vulnerability of RF systems to relay attacks, where an intermediary device intercepts and retransmits signals, potentially altering or delaying them. Such attacks can compromise security and reliability in wireless communications. The method involves using a hardware processor to receive an RF transmission via a first transceiver. The system then detects potential relay or MITM attacks by analyzing AGC distortion in the received signal. This is done by extracting a rise transient from the beginning of the transmission to the start of the data region. The system estimates the differential AGC distortion caused by its own receiver, based on the known behavior of its AGC circuit. If the received transmission exhibits greater AGC distortion than the estimated differential distortion, it indicates the presence of an additional AGC stage from a relaying or replaying transceiver, suggesting a relay or MITM attack. This approach leverages the inherent distortion introduced by multiple AGC stages to identify unauthorized intermediaries in the communication path. The technique enhances security by detecting anomalies in signal processing that are characteristic of relay attacks.
9. The method of claim 8 , wherein estimating the differential AGC distortion caused by the receiver and determining whether the received RF transmission exhibits greater AGC distortion than the differential AGC distortion includes measuring mean power of complex column sample vector.
This invention relates to wireless communication systems, specifically to methods for estimating and mitigating automatic gain control (AGC) distortion in received radio frequency (RF) transmissions. The problem addressed is the distortion introduced by AGC mechanisms in receivers, which can degrade signal quality and affect demodulation performance. The invention provides a technique to quantify and compensate for this distortion by comparing the distortion in the received signal against a reference distortion level. The method involves measuring the mean power of a complex column sample vector derived from the received RF transmission. This measurement is used to estimate the differential AGC distortion caused by the receiver's own AGC circuitry. The estimated distortion is then compared to the actual distortion observed in the received signal to determine whether the signal exhibits greater distortion than expected. If the received signal's distortion exceeds the estimated differential AGC distortion, corrective measures can be applied to improve signal quality. The technique ensures that the receiver can accurately assess and compensate for AGC-induced distortions, enhancing overall communication reliability.
10. The method of claim 8 , wherein detecting double-AGC distortion further comprises: finding and extracting samples of the received RF transmission including: before the beginning of the rise transient; after a fall transient; and from frequencies out of a bandwidth of the received RF transmission during a data transmission section of the received RF transmission.
This invention relates to detecting double automatic gain control (AGC) distortion in received radio frequency (RF) transmissions. The problem addressed is the difficulty in accurately identifying and mitigating AGC-related distortions that can degrade signal quality in wireless communications. The method involves analyzing specific segments of the RF transmission to detect distortion caused by AGC adjustments. The process begins by identifying and extracting samples from the received RF transmission at key points: before the rise transient, after the fall transient, and from frequencies outside the transmission's bandwidth during the data transmission section. The rise and fall transients are transitions in signal amplitude that occur at the start and end of a transmission burst, respectively. By examining these regions, the method can detect distortions introduced by AGC adjustments that occur during these transitions. Additionally, analyzing frequencies outside the transmission bandwidth helps identify interference or distortion that may not be apparent within the primary signal bandwidth. The extracted samples are then used to assess the presence and severity of double-AGC distortion, which occurs when the AGC system overcompensates for signal variations, leading to amplitude fluctuations that degrade signal integrity. This detection method improves the accuracy of distortion identification, enabling better signal processing and error correction in wireless communication systems. The approach is particularly useful in environments where signal conditions vary rapidly, such as in mobile or high-interference scenarios.
11. The method of claim 10 , wherein the samples are extracted by using a high pass filter with a cutoff frequency that is higher than the bandwidth of the received RF transmission.
This invention relates to signal processing in radio frequency (RF) communication systems, specifically addressing the challenge of extracting samples from an RF transmission while minimizing interference from unwanted signal components. The method involves filtering the received RF transmission using a high pass filter with a cutoff frequency set higher than the bandwidth of the transmission. This ensures that only the relevant high-frequency components of the signal are retained, effectively suppressing lower-frequency noise and interference. The filtered signal is then sampled to obtain a set of data points that accurately represent the desired RF transmission without distortion from out-of-band signals. This approach improves signal fidelity and reduces processing complexity by focusing on the frequency range of interest. The method is particularly useful in applications where precise signal extraction is critical, such as in wireless communication systems, radar, and other RF-based technologies. By dynamically adjusting the cutoff frequency based on the transmission bandwidth, the system can adapt to varying signal conditions, ensuring optimal performance across different operating environments. The technique enhances signal integrity and reliability, making it suitable for high-precision applications where interference mitigation is essential.
12. The method of claim 8 , wherein detecting double-AGC distortion further comprises: determining that the received RF transmission was not relayed or replayed by determining that the received RF transmission was not previously distorted by a AGC stage of another RF device prior to the first RF receiver receiving the RF transmission.
This invention relates to radio frequency (RF) communication systems and addresses the problem of detecting double automatic gain control (AGC) distortion in received RF transmissions. AGC stages in RF devices adjust signal levels to optimize reception, but when a transmission is relayed or replayed through multiple devices, repeated AGC processing can distort the signal, degrading performance. The invention provides a method to detect such distortion by analyzing the received RF transmission to determine whether it has undergone prior AGC processing. Specifically, the method involves examining the transmission to identify characteristics indicative of prior AGC distortion, such as unnatural amplitude variations or gain adjustments. If the transmission shows no signs of prior AGC processing, it is determined to be a direct transmission rather than a relayed or replayed one. This detection helps maintain signal integrity and improves the reliability of RF communication systems by ensuring that only undistorted transmissions are processed further. The method is particularly useful in applications where signal fidelity is critical, such as secure communications or high-precision RF systems.
13. The method of claim 8 , wherein the detecting double-AGC distortion further comprises: training one or more machine learning classifiers for detecting double-AGC distortion with a set of clean signals, which are signals that not distorted by an AGC circuit.
This invention relates to signal processing, specifically detecting distortion caused by automatic gain control (AGC) circuits in communication systems. AGC circuits adjust signal amplitude to maintain consistent levels, but can introduce distortion when multiple AGC stages are misconfigured or improperly synchronized, a condition known as double-AGC distortion. This distortion degrades signal quality and can lead to communication errors. The method involves training machine learning classifiers to identify double-AGC distortion by using a dataset of clean signals—those not distorted by AGC circuits. The classifiers are trained to recognize patterns indicative of double-AGC distortion, allowing for accurate detection in real-world signals. This approach improves signal integrity by enabling systems to identify and mitigate distortion caused by improper AGC operation. The method may be applied in various communication systems where AGC circuits are used, such as wireless networks, audio processing, or other signal transmission environments. By leveraging machine learning, the system can adapt to different signal conditions and improve detection accuracy over time.
14. The method of claim 8 , wherein detecting double-AGC distortion further comprises at least one of: determining a noise mean power; assuming an underlying Rayleigh model and performing a parameter estimation by a Maximum Likelihood or a Method of Moments approach; or assuming a real normal model and calculating variances, an average and squared root.
This invention relates to signal processing, specifically detecting distortion in automatic gain control (AGC) systems, which can degrade signal quality in communication and radar systems. The method addresses the challenge of identifying double-AGC distortion, where multiple gain adjustments introduce artifacts that distort the signal's amplitude distribution. The method involves analyzing the signal to detect such distortion by evaluating statistical properties of the signal. One approach measures the noise mean power to identify deviations indicative of distortion. Another method assumes the signal follows a Rayleigh distribution and estimates its parameters using statistical techniques like Maximum Likelihood or the Method of Moments. A third approach assumes the signal is normally distributed and calculates its variance, average, and square root to detect anomalies. These techniques help distinguish between normal signal variations and distortion caused by improper AGC adjustments. The method improves signal integrity by enabling early detection and correction of AGC-related artifacts, enhancing performance in communication and radar applications.
15. A computer program product comprising a non-transitory computer-readable storage medium having program instructions embodied therewith, the program instructions executable by at least one hardware processor to: receive, using a first transceiver, a radio-frequency (RF) transmission from an RF device; and detect a second transceiver performing a relay or man-in-the-middle (MITM) attack by: detecting double-Automatic Gain Control (AGC) distortion effect in the received RF transmission by: finding and extracting a rise transient from a beginning to a start of a data region of the received RF transmission; estimating a differential AGC distortion caused by the receiver, based on the known output of an AGC circuit if the system; and determining whether the received RF transmission exhibits greater AGC distortion than the differential AGC distortion such as to indicate distortion from a relay or replay AGC stage of the second transceiver.
This invention relates to detecting relay or man-in-the-middle (MITM) attacks in radio-frequency (RF) transmissions. The problem addressed is the vulnerability of wireless communication systems to relay attacks, where an intermediary device intercepts and retransmits signals, potentially compromising security and integrity. The solution involves analyzing RF transmissions to identify distortions caused by relay devices. The system receives an RF transmission from an RF device using a first transceiver. It then detects potential relay or MITM attacks by analyzing Automatic Gain Control (AGC) distortion in the received signal. The detection process involves extracting a rise transient from the beginning of the transmission to the start of the data region. The system estimates the differential AGC distortion caused by its own receiver, based on the known output of its AGC circuit. By comparing the observed AGC distortion in the received transmission to the expected differential AGC distortion, the system determines whether the transmission exhibits excessive distortion indicative of a relay or replay AGC stage from a second transceiver. This method helps identify unauthorized relay devices by detecting anomalies in the signal's gain control behavior.
16. The computer program product of claim 15 , wherein estimating the differential AGC distortion caused by the receiver and determining whether the received RF transmission exhibits greater AGC distortion than the differential AGC distortion includes measuring mean power of complex column sample vector.
This invention relates to wireless communication systems, specifically addressing the problem of automatic gain control (AGC) distortion in received radio frequency (RF) transmissions. AGC distortion occurs when the receiver's gain adjustment introduces nonlinearities, degrading signal quality. The invention provides a method to estimate and mitigate this distortion by analyzing the received RF transmission. The technique involves measuring the mean power of a complex column sample vector derived from the received signal. This measurement is used to estimate the differential AGC distortion caused by the receiver's own gain control mechanisms. By comparing the estimated distortion with the actual distortion observed in the received transmission, the system determines whether the signal exhibits excessive AGC distortion. If the distortion exceeds a threshold, corrective measures can be applied to improve signal integrity. The method leverages signal processing techniques to isolate and quantify AGC-related artifacts, ensuring accurate assessment of distortion levels. This approach enhances receiver performance by dynamically adjusting gain control parameters to minimize distortion, thereby improving signal fidelity and communication reliability. The invention is particularly useful in environments where signal quality is critical, such as high-speed data transmissions or interference-prone scenarios.
17. The computer program product of claim 15 , wherein detecting double-AGC distortion further comprises: finding and extracting samples of the received RF transmission including: before the beginning of the rise transient; after a fall transient; and from frequencies out of a bandwidth of the received RF transmission during a data transmission section of the received RF transmission, wherein the samples are extracted by using a high pass filter with a cutoff frequency that is higher than the bandwidth of the received RF transmission.
This invention relates to detecting double automatic gain control (AGC) distortion in radio frequency (RF) transmissions, a problem that arises when AGC systems fail to properly adjust gain, leading to signal distortion. The invention provides a method for identifying and mitigating such distortion by analyzing specific segments of the RF transmission. The process involves extracting samples from three distinct regions: before the rise transient, after the fall transient, and from frequencies outside the transmission bandwidth during the data section. These samples are obtained using a high-pass filter with a cutoff frequency higher than the transmission bandwidth, ensuring that only relevant distortion artifacts are captured. By analyzing these samples, the system can detect and correct double-AGC distortion, improving signal integrity in RF communications. The method is particularly useful in applications where signal quality is critical, such as wireless networks, satellite communications, and radar systems. The use of a high-pass filter ensures that the extracted samples are free from in-band interference, allowing for accurate distortion detection. This approach enhances the reliability of RF transmission systems by providing a robust mechanism for identifying and mitigating AGC-related distortions.
18. The computer program product of claim 15 , wherein detecting double-AGC distortion further comprises: determining that the received RF transmission was not relayed or replayed by determining that the received RF transmission was not previously distorted by a AGC stage of another RF device prior to the first RF receiver receiving the RF transmission.
This invention relates to radio frequency (RF) signal processing, specifically detecting distortion caused by automatic gain control (AGC) in RF transmissions. The problem addressed is identifying whether an RF signal has been relayed or replayed by another RF device, which can introduce additional AGC distortion. The solution involves analyzing the received RF transmission to determine if it has undergone prior AGC processing by another RF device before reaching the first RF receiver. This is done by examining the signal for characteristics indicative of multiple AGC stages, such as inconsistent gain adjustments or distortion patterns that would not occur in a direct transmission. The method helps distinguish between direct transmissions and those that have been relayed or replayed, which is useful for security, signal integrity, and network diagnostics. The invention is implemented as a computer program product that processes the RF signal data to detect these distortions, ensuring accurate identification of relayed or replayed transmissions.
19. The computer program product of claim 15 , wherein detecting double-AGC distortion further comprises: training one or more machine learning classifiers for detecting double-AGC distortion with a set of clean signals, which are signals that not distorted by an AGC circuit.
This invention relates to signal processing, specifically detecting distortion caused by automatic gain control (AGC) circuits in communication systems. AGC circuits are used to maintain signal amplitude within a desired range, but they can introduce distortion when signals are processed multiple times, a phenomenon known as double-AGC distortion. This distortion degrades signal quality and can lead to errors in data transmission. The invention involves a method for detecting double-AGC distortion using machine learning. A set of clean signals, which are signals not distorted by an AGC circuit, is used to train one or more machine learning classifiers. These classifiers are then employed to identify instances of double-AGC distortion in processed signals. The training process ensures that the classifiers can distinguish between normal signal variations and distortion caused by repeated AGC processing. This approach improves signal integrity by enabling early detection and correction of distortion, enhancing the reliability of communication systems. The method is particularly useful in applications where signals undergo multiple stages of amplification or processing, such as in wireless communication networks or audio systems.
20. The computer program product of claim 15 , wherein detecting double-AGC distortion further comprises: determining a noise mean power; assuming an underlying Rayleigh model and performing a parameter estimation by a Maximum Likelihood or a Method of Moments approach; or assuming a real normal model and calculating variances, an average and squared root.
This invention relates to signal processing, specifically detecting and mitigating double-AGC (Automatic Gain Control) distortion in communication systems. The problem addressed is the degradation of signal quality due to double-AGC distortion, which occurs when multiple AGC stages are applied to a signal, leading to non-linear distortions that affect signal integrity and performance. The invention provides a method for detecting double-AGC distortion in received signals. The process involves analyzing the signal to determine a noise mean power. To assess distortion, the method employs statistical modeling approaches. One approach assumes an underlying Rayleigh distribution for the signal and performs parameter estimation using either a Maximum Likelihood method or a Method of Moments. Alternatively, the method assumes a real normal (Gaussian) distribution model and calculates statistical parameters such as variances, averages, and the square root of these values to identify distortion. These techniques help quantify the extent of distortion caused by multiple AGC stages, enabling corrective measures to be applied to improve signal quality. The invention is implemented as a computer program product, integrating these detection algorithms into signal processing systems to enhance communication reliability.
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March 17, 2020
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